Background: Somatosensory function plays an important role in motor learning. More than half of the stroke patients have somatosensory impairments in the upper limb, which could hamper recovery.Question: Is sensorimotor upper limb (UL) therapy of more benefit for motor and somatosensory outcome than motor therapy?Design: Randomized assessor- blinded multicenter controlled trial with block randomization stratified for neglect, severity of motor impairment, and type of stroke.Participants: 40 first-ever stroke patients with UL sensorimotor impairments admitted to the rehabilitation center.Intervention: Both groups received 16 h of additional therapy over 4 weeks consisting of sensorimotor (N = 22) or motor (N = 18) UL therapy.Outcome measures: Action Research Arm test (ARAT) as primary outcome, and other motor and somatosensory measures were assessed at baseline, post-intervention and after 4 weeks follow-up.Results: No significant between-group differences were found for change scores in ARAT or any somatosensory measure between the three time points. For UL impairment (Fugl-Meyer assessment), a significant greater improvement was found for the motor group compared to the sensorimotor group from baseline to post-intervention [mean (SD) improvement 14.65 (2.19) vs. 5.99 (2.06); p = 0.01] and from baseline to follow-up [17.38 (2.37) vs. 6.75 (2.29); p = 0.003].Conclusion: UL motor therapy may improve motor impairment more than UL sensorimotor therapy in patients with sensorimotor impairments in the early rehabilitation phase post stroke. For these patients, integrated sensorimotor therapy may not improve somatosensory function and may be less effective for motor recovery.Clinical Trial Registration:www.ClinicalTrials.gov, identifier NCT03236376.

Upper limb sensory processing deficits are common in the chronic phase after stroke and are associated with decreased functional performance. Yet, current clinical assessments show suboptimal psychometric properties. Our aim was to develop and validate a novel robot-based assessment of sensory processing. We assessed 60 healthy participants and 20 participants with chronic stroke using existing clinical and robot-based assessments of sensorimotor function. In addition, sensory processing was evaluated with a new evaluation protocol, using a bimanual planar robot, through passive or active exploration, reproduction and identification of 15 geometrical shapes. The discriminative validity of this novel assessment was evaluated by comparing the performance between healthy participants and participants with stroke, and the convergent validity was evaluated by calculating the correlation coefficients with existing assessments for people with stroke. The results showed that participants with stroke showed a significantly worse sensory processing ability than healthy participants (passive condition: p = 0.028, Hedges’ g = 0.58; active condition: p = 0.012, Hedges’ g = 0.73), as shown by the less accurate reproduction and identification of shapes. The novel assessment showed moderate to high correlations with the tactile discrimination test: a sensitive clinical assessment of sensory processing (r = 0.52–0.71). We conclude that the novel robot-based sensory processing assessment shows good discriminant and convergent validity for use in participants with chronic stroke.

Somatosensory function plays an important role for upper limb motor learning. However, knowledge about underlying mechanisms of sensorimotor therapy is lacking. We aim to investigate differences in therapy-induced resting state functional connectivity changes between additional sensorimotor compared to motor therapy in the early phase post stroke. Thirty first-stroke patients with a sensorimotor impairment were included for an assessor-blinded multi-centre randomized controlled trial within eight weeks post stroke (13 (43%) females; mean age: 67 ± 13 years; mean time post stroke: 43 ± 13 days). Patients were randomly assigned to additional sensorimotor (n = 18) or motor (n = 12) therapy, receiving 16 hours of additional therapy within 4 weeks. Sensorimotor evaluations and resting state functional magnetic resonance imaging (fMRI) were performed at baseline (T1), post-intervention (T2) and after four weeks follow-up (T3). Resting-state fMRI was also performed in an age-matched healthy control group (n = 19) to identify patterns of aberrant connectivity in stroke patients between hemispheres, or within ipsilesional and contralesional hemispheres. Mixed model analysis investigated session and treatment effects between stroke therapy groups. Non-parametric partial correlations were used to investigate brain-behaviour associations with age and frame wise displacement as nuisance regressors. Connections within the contralesional hemisphere that showed hypo-connectivity in subacute stroke patients (compared to healthy controls) showed a trend towards a more pronounced pre-to-post normalization (less hypo-connectivity) in the motor therapy group, compared to the sensorimotor therapy group (mean estimated difference= -0.155 ± 0.061; p = 0.02). Further, the motor therapy group also tended to show a further pre-to-post increase in functional connectivity strength among connections that already showed hyper-connectivity in the stroke patients at baseline versus healthy controls (mean estimated difference= -0.144 ± 0.072; p = 0.06). Notably, these observed increases in hyper-connectivity of the contralesional hemisphere were positively associated with improvements in functional activity (r = 0.48), providing indications that these patterns of hyper-connectivity are compensatory in nature. The sensorimotor and motor therapy group showed no significant differences in terms of pre-to-post changes in inter-hemispheric connectivity or ipsilesional intrahemispheric connectivity. While effects are only tentative within this preliminary sample, results suggest a possible stronger normalisation of hypo-connectivity and a stronger pre-to-post increase in compensatory hyper-connectivity of the contralesional hemisphere after motor therapy compared to sensorimotor therapy. Future studies with larger patient samples are however recommended to confirm these trend-based preliminary findings.

Sensory processing consists in the integration and interpretation of somatosensory information. It builds upon proprioception but is a distinct function requiring complex processing by the brain over time. Currently little is known about the effect of aging on sensory processing ability, nor the influence of other covariates such as motor function, proprioception, or cognition. In this study, we measured upper limb passive and active sensory processing, motor function, proprioception, and cognition in 40 healthy younger adults and 54 older adults. We analyzed age differences across all measures and evaluated the influence of covariates on sensory processing through regression. Our results showed larger effect sizes for age differences in sensory processing (r=0.39-0.40) compared to motor function (r=0.18-0.22) and proprioception (r=0.10-0.27), but smaller than for cognition (r=0.56-0.63). Aside from age, we found no evidence that sensory processing performance was influenced by motor function or proprioception, but active sensory processing was influenced by cognition (β=0.32-0.46). In conclusion, sensory processing showed an age-related decline, while some proprioceptive and motor abilities were preserved across age.

Background. Altered dynamic functional connectivity has been associated with motor impairments in the acute phase post-stroke. Its association with somatosensory impairments in the early sub-acute phase remains unexplored. Objective. To investigate altered dynamic functional connectivity associated with somatosensory impairments in the early sub-acute phase post-stroke. Methods. We collected resting state magnetic resonance imaging and clinical somatosensory function of the upper limb of 20 subacute stroke patients and 16 healthy controls (HC). A sliding-window approach was used to identify 3 connectivity states based on the estimated dynamic functional connectivity of sensorimotor related networks. Network components were subdivided into 3 domains: cortical and subcortical sensorimotor, as well as cognitive control network. Between-group differences were investigated using independent t-tests and Mann–Whitney- U tests. Analyzes were performed with correction for age, head motion and time post-stroke and corrected for multiple comparisons. Results. Stroke patients spent significantly less time in a weakly connected network state (state 3; dwell time: pstate3 = 0.003, meanstroke = 53.02, SDstroke = 53.13; meanHC = 118.92, SDHC = 72.84), and stayed shorter but more time intervals in a highly connected intra-domain network state (state 1; fraction time: pstate 1 < 0.001, meanstroke = 0.46, SDstroke = 0.26; meanHC = 0.26, SDHC = 0.21) compared to HC. After 8 weeks of therapy, improvements in wrist proprioception were moderately associated with decreases in dwell and fraction times toward a more normalized pattern. Conclusion. Changes in temporal properties of large-scale network interactions are present in the early rehabilitation phase post-stroke and could indicate enhanced neural plasticity. These findings could augment the understanding of cerebral reorganization after loss of neural tissue specialized in somatosensory functions.